Design And Implementation Of Milk Source Quality Monitoring And Analysis System

With the high openness of the Chinese dairy market,the relationship between domestic dairy yield and the international dairy market has become closer.In recent years,due to the impact of imported dairy products,the domestic dairy industry has been in a downturn,in which the pastures and dairy companies suffered the most.Some studies have shown that milk source quality and milk yield are the main reasons for the lack of competitiveness in the domestic dairy industry.Therefore,it is of great significance to research the quality monitoring of milk source and the prediction of milk yield for the development of dairy industry in China.In order to solve the problems of untimely monitoring of milk source quality and low accuracy prediction of milk yield in the domestic dairy industry,this paper comprehensively analyzes relevant research approach at home and abroad,and designs the high-efficiency milk source quality monitoring system and milk yield prediction models.The monitoring system can effectively control the quality of the original milk source and provide strong support for the analysis of milk source data;The predictive model accurately predicts milk yield and provides a reliable basis for pasture breeding and milk yield scheduling.The main research work of this thesis is summarized as follows:1.Design and implementation of milk source quality monitoring and management platform.(1)Milk source temperature monitoring subsystem.In order to solve the problem of low efficiency of milk source quality monitoring,this paper designs a milk source temperature monitoring system to monitor the temperature of the milk source.In order to meet the diverse needs of users,the system provides two access methods: Web and WeChat applet.This paper uses sensor technology to collect milk source temperature.These temperature data are remotely transmitted to the cloud server and stored in a database for real-time temperature monitoring.The visualization part of the subsystem is mainly composed of a user login module,a user management module,a temperature monitoring module,a high temperature warning module,and a temperature statistics module.The milk source temperature monitoring subsystem can effectively ensure the quality of the milk source and improve the safety of the milk source.(2)Cow growth information monitoring subsystem.In order to solve the low Informa ionization of cow growth information monitoring,this paper designs a cow growth information monitoring subsystem to monitor the growth process of cows.Similarly,the system provides two access methods: Web and WeChat applet.The subsystem is mainly composed of three modules: cow basic information management,veterinary drug information management and feed information management.The cow growth information monitoring subsystem collects relevant information from the cow's growth process and provides reliable data support for breeding and milk yield scheduling.2.Design and implementation of prediction model of milk yield based on neural network.(1)Using the GA-LSTM recurrent neural networks algorithm to explore the relationship between cow growth information and milk yield.Based on this,it is possible to predict the milk yield per day,which provides a decision for milk delivery scheduling.(2)Using the MA-BP neural network algorithm to mine the relationship between the initial 90-day milk yield from primiparous cows and the 305-day total milk yield.Based on this,it is possible to predict the milk yield of 305 days of primiparous cows,which provides more valuable guidance for the breeding of cows.